{"id":"W4417344491","doi":"10.1007/s10462-025-11400-w","title":"A review of network delay prediction and advances in large language models for air traffic","year":2025,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"Air Traffic Management and Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Jiangsu Province; China Scholarship Council; Government of Jiangsu Province; Nanjing University of Aeronautics and Astronautics; China Postdoctoral Science Foundation","keywords":"Causal inference; Causality (physics); Deep learning; Artificial neural network; Inference; Air traffic control; Network topology; Graph; Learning network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005032339,0.00009638206,0.0002767973,0.0000513355,0.00002454483,0.000004557863,0.00007641785,0.00003142887,0.00002059039],"category_scores_gemma":[0.00005311649,0.0000912722,0.00005474261,0.0004483472,0.00001566317,0.0001770454,0.00001436362,0.00005514178,0.0000018966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001718634,"about_ca_system_score_gemma":0.000008524214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.894923e-7,"about_ca_topic_score_gemma":0.00005218744,"domain_scores_codex":[0.999157,0.00002534938,0.000478444,0.0001316262,0.00005488888,0.000152651],"domain_scores_gemma":[0.9997274,0.00005495927,0.0000471718,0.0001170114,0.00003592008,0.00001753583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003289774,0.00001634168,0.000004470592,0.04049521,0.000009654716,2.874569e-7,0.00004661455,0.4185961,6.860824e-7,0.01205792,0.001143922,0.5276255],"study_design_scores_gemma":[0.00002393281,0.00002043278,0.000002989798,0.04911045,0.00008175837,3.18851e-7,0.00004806309,0.9199264,0.00002957073,0.001440499,0.02922054,0.0000950409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006783765,0.638755,0.3595581,0.0001131046,0.00009377343,0.0006879576,0.000005991412,0.00005060125,0.0006676142],"genre_scores_gemma":[0.04237528,0.9553826,0.00160713,0.0004295515,0.00002883428,0.0001197394,0.00003015208,0.000008470811,0.00001822433],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5275305,"threshold_uncertainty_score":0.3721972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01670916189376542,"score_gpt":0.2886140109507852,"score_spread":0.2719048490570198,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}